{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import mean_squared_error\n",
    "\n",
    "import xgboost as xgb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def notEmpty(s):\n",
    "    return s != ''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "names = [\n",
    "    'CRIM', 'ZN', 'INDUS', 'CHAS', 'NOX', 'RM', \n",
    "    'AGE', 'DIS', 'RAD', 'TAX', 'PTRATIO', 'B', \n",
    "    'LSTAT'\n",
    "]\n",
    "path = \"datas/zhengqi_train.txt\"\n",
    "# 由于数据文件格式不统一,所以读取的时候,\n",
    "# 先按照一行一个字段属性读取数据,然后再按照每行数据进行处理\n",
    "fd = pd.read_csv(path, sep='\\s+', header=0)\n",
    "x, y = np.split(fd, (38,), axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2888 entries, 0 to 2887\n",
      "Data columns (total 38 columns):\n",
      "V0     2888 non-null float64\n",
      "V1     2888 non-null float64\n",
      "V2     2888 non-null float64\n",
      "V3     2888 non-null float64\n",
      "V4     2888 non-null float64\n",
      "V5     2888 non-null float64\n",
      "V6     2888 non-null float64\n",
      "V7     2888 non-null float64\n",
      "V8     2888 non-null float64\n",
      "V9     2888 non-null float64\n",
      "V10    2888 non-null float64\n",
      "V11    2888 non-null float64\n",
      "V12    2888 non-null float64\n",
      "V13    2888 non-null float64\n",
      "V14    2888 non-null float64\n",
      "V15    2888 non-null float64\n",
      "V16    2888 non-null float64\n",
      "V17    2888 non-null float64\n",
      "V18    2888 non-null float64\n",
      "V19    2888 non-null float64\n",
      "V20    2888 non-null float64\n",
      "V21    2888 non-null float64\n",
      "V22    2888 non-null float64\n",
      "V23    2888 non-null float64\n",
      "V24    2888 non-null float64\n",
      "V25    2888 non-null float64\n",
      "V26    2888 non-null float64\n",
      "V27    2888 non-null float64\n",
      "V28    2888 non-null float64\n",
      "V29    2888 non-null float64\n",
      "V30    2888 non-null float64\n",
      "V31    2888 non-null float64\n",
      "V32    2888 non-null float64\n",
      "V33    2888 non-null float64\n",
      "V34    2888 non-null float64\n",
      "V35    2888 non-null float64\n",
      "V36    2888 non-null float64\n",
      "V37    2888 non-null float64\n",
      "dtypes: float64(38)\n",
      "memory usage: 857.5 KB\n"
     ]
    },
    {
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       "      <td>-4.789</td>\n",
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       "      <td>0.968</td>\n",
       "      <td>0.437</td>\n",
       "      <td>0.066</td>\n",
       "      <td>0.566</td>\n",
       "      <td>0.194</td>\n",
       "      <td>-0.893</td>\n",
       "      <td>-1.566</td>\n",
       "      <td>-2.360</td>\n",
       "      <td>0.332</td>\n",
       "      <td>-2.114</td>\n",
       "      <td>...</td>\n",
       "      <td>0.671</td>\n",
       "      <td>-0.128</td>\n",
       "      <td>0.124</td>\n",
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       "      <td>0.568</td>\n",
       "      <td>0.235</td>\n",
       "      <td>0.370</td>\n",
       "      <td>0.112</td>\n",
       "      <td>-0.797</td>\n",
       "      <td>-1.367</td>\n",
       "      <td>-2.360</td>\n",
       "      <td>0.396</td>\n",
       "      <td>-2.114</td>\n",
       "      <td>...</td>\n",
       "      <td>1.287</td>\n",
       "      <td>-0.009</td>\n",
       "      <td>0.361</td>\n",
       "      <td>0.277</td>\n",
       "      <td>-0.116</td>\n",
       "      <td>-0.843</td>\n",
       "      <td>0.160</td>\n",
       "      <td>0.364</td>\n",
       "      <td>0.765</td>\n",
       "      <td>-0.589</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.733</td>\n",
       "      <td>0.368</td>\n",
       "      <td>0.283</td>\n",
       "      <td>0.165</td>\n",
       "      <td>0.599</td>\n",
       "      <td>-0.679</td>\n",
       "      <td>-1.200</td>\n",
       "      <td>-2.086</td>\n",
       "      <td>0.403</td>\n",
       "      <td>-2.114</td>\n",
       "      <td>...</td>\n",
       "      <td>1.298</td>\n",
       "      <td>0.015</td>\n",
       "      <td>0.417</td>\n",
       "      <td>0.279</td>\n",
       "      <td>0.603</td>\n",
       "      <td>-0.843</td>\n",
       "      <td>-0.065</td>\n",
       "      <td>0.364</td>\n",
       "      <td>0.333</td>\n",
       "      <td>-0.112</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.684</td>\n",
       "      <td>0.638</td>\n",
       "      <td>0.260</td>\n",
       "      <td>0.209</td>\n",
       "      <td>0.337</td>\n",
       "      <td>-0.454</td>\n",
       "      <td>-1.073</td>\n",
       "      <td>-2.086</td>\n",
       "      <td>0.314</td>\n",
       "      <td>-2.114</td>\n",
       "      <td>...</td>\n",
       "      <td>1.289</td>\n",
       "      <td>0.183</td>\n",
       "      <td>1.078</td>\n",
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       "      <td>0.418</td>\n",
       "      <td>-0.843</td>\n",
       "      <td>-0.215</td>\n",
       "      <td>0.364</td>\n",
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       "      <td>-0.028</td>\n",
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       "      V0     V1     V2     V3     V4     V5     V6     V7     V8     V9  \\\n",
       "0  0.566  0.016 -0.143  0.407  0.452 -0.901 -1.812 -2.360 -0.436 -2.114   \n",
       "1  0.968  0.437  0.066  0.566  0.194 -0.893 -1.566 -2.360  0.332 -2.114   \n",
       "2  1.013  0.568  0.235  0.370  0.112 -0.797 -1.367 -2.360  0.396 -2.114   \n",
       "3  0.733  0.368  0.283  0.165  0.599 -0.679 -1.200 -2.086  0.403 -2.114   \n",
       "4  0.684  0.638  0.260  0.209  0.337 -0.454 -1.073 -2.086  0.314 -2.114   \n",
       "\n",
       "   ...      V28    V29    V30    V31    V32    V33    V34    V35    V36    V37  \n",
       "0  ...   -0.450  0.136  0.109 -0.615  0.327 -4.627 -4.789 -5.101 -2.608 -3.508  \n",
       "1  ...    0.671 -0.128  0.124  0.032  0.600 -0.843  0.160  0.364 -0.335 -0.730  \n",
       "2  ...    1.287 -0.009  0.361  0.277 -0.116 -0.843  0.160  0.364  0.765 -0.589  \n",
       "3  ...    1.298  0.015  0.417  0.279  0.603 -0.843 -0.065  0.364  0.333 -0.112  \n",
       "4  ...    1.289  0.183  1.078  0.328  0.418 -0.843 -0.215  0.364 -0.280 -0.028  \n",
       "\n",
       "[5 rows x 38 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 查看数据信息\n",
    "X_DF = pd.DataFrame(x)\n",
    "X_DF.info()\n",
    "X_DF.describe().T\n",
    "X_DF.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "训练数据集样本数目:2310, 测试数据集样本数目:578\n"
     ]
    }
   ],
   "source": [
    "# 数据的分割,\n",
    "x_train, x_test, y_train, y_test = train_test_split(\n",
    "    x,y, \n",
    "    train_size=0.8, \n",
    "    random_state=14\n",
    ")\n",
    "print(\n",
    "    \"训练数据集样本数目:%d, 测试数据集样本数目:%d\" \n",
    "    % \n",
    "    (x_train.shape[0], x_test.shape[0])\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "# XGBoost将数据转换为XGBoost可用的数据类型\n",
    "dtrain = xgb.DMatrix(x_train, label=y_train)\n",
    "dtest = xgb.DMatrix(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "38"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dtrain.num_col()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2310"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dtrain.num_row()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "578"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dtest.num_row()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "38"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dtest.num_col()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "# XGBoost模型构建\n",
    "# 1. 参数构建\n",
    "params = {\n",
    "    'max_depth': 6, \n",
    "    'eta':0.3, \n",
    "    'silent':1, \n",
    "    'objective':'reg:linear'\n",
    "}\n",
    "num_round = 2\n",
    "# 2. 模型训练\n",
    "bst = xgb.train(params, dtrain, num_round)\n",
    "# 3. 模型保存\n",
    "bst.save_model('xgb.model')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.36529016557729027\n"
     ]
    }
   ],
   "source": [
    "# XGBoost模型预测\n",
    "y_pred = bst.predict(dtest)\n",
    "print(mean_squared_error(y_pred, y_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mean_squared_error = 968.652027\n"
     ]
    }
   ],
   "source": [
    "# 4. 加载模型\n",
    "bst2 = xgb.Booster()\n",
    "bst2.load_model('xgb.model')\n",
    "# 5 使用加载模型预测\n",
    "y_pred2 = bst2.predict(dtest)\n",
    "print('mean_squared_error = %f' % mean_squared_error(y_pred2, y_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 画图\n",
    "# 7. 画图 \n",
    "plt.figure(figsize=(12, 6), facecolor='w')\n",
    "ln_x_test = range(len(x_test))\n",
    "\n",
    "plt.plot(ln_x_test, y_test, 'r-', lw=2, label=u'实际值')\n",
    "plt.plot(ln_x_test, y_pred, 'g-', lw=4, label=u'XGBoost模型')\n",
    "\n",
    "plt.xlabel(u'数据编码')\n",
    "plt.ylabel(u'租赁价格')\n",
    "\n",
    "plt.legend(loc='lower right')\n",
    "plt.grid(True)\n",
    "plt.title(u'工业蒸汽量预测')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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1Kvd5vYiIwWCQtLQ02bJli7z22msiIvL6669Lenq6iIgsW7ZM2rZtK+Hh4UXarVixQry8vERExN/fX+Lj4yU1NVVatWolV65ckUceeURSUlKKtPH19ZWTJ0/K6dOnxdvbW0SMm6vl5OTIzz//LEOHDhURkU6dOklGRoZ8/vnnMmTIEMnPz5fu3bvLlStXZOnSpTJ+/HgREQkICCiRT/G2Fy5ckIYNG0peXp5ERkbK66+/Xv6HXQ6u/IxcxLXzr45zBMV1BFuBPabXmkpG06ZNGT9+PAC1a9emQYMGXLp0CREhJyeH2rVrc+eddzJy5EhznfI4duwY7u7uNGzYkE2bNnHw4EF69uzJ+fPncXd35/z583z88cdWn/fv2LGDAQMGkJuby/79+/Hx8aFZs2bceOONHDp0CIBnnnmGO++8k2+++QYANzc3Ll26RFZWlvlu4rrrriMnJ6dI2SuvvEL9+vXNOSilWL9+PUopzpw5g7u7O2BcwdG7d288PT1JTEy02lZEyM3NJS8vDxHhl19+ubYvQKNxAs7QEQwSkQillM2Gm1pH4BgdQfI7obRv3x4wPvrIy8tj2LBh+Pv7s2zZMkJCQmjbtq25/kcffYSXl1e5a/bXrFlDaGgoAGfOnKFTp05ERkbSunVrXn75Zf79738zY8YMjh8/XqJtfHw877//Pmlpadx4443m8vr165OWlsbDDz9MQEAAWVlZ3HvvvTz66KO88847BAQEICKsWrUKgNdff51OnTpRUFDA9u3bAXjsscc4c+YMs2fP5rPPPqNGjRo0atSIuXPn8sYbb7Br1y4Ann76acaMGcOiRYuYNWsWX3zxRYm29evXZ8aMGYSGhnLXXXeRnZ39D74Jjcax2H0gEJF9Sqm2pl1HrxeRE7a0K6Yj4Nt+de0ZZqUmKyuLLxyQf+FkbFxcHMuWLePtt99mzJgx9OrVi9DQUMLDw5k7dy6dOnVi9erV7Nmzh+nTp5droPHVV1/xwgsvEBMTQ0ZGBs2bN2fbtm3Ur1+fH374gbVr17Jz507S0tK4fPkyDRo0oHPnzuTl5XH06FEuXrzI/v37OX/+vPlaJ0+e5OjRo7i5uXHo0CEuX77MqVOniImJ4emnn2bBggVcuXKFkSNH8vHHHzNlyhQWLlzIqVOnGDJkCLNmzSIjI4MpU6bw7LPPcuHCBTZu3Eh2djadOnXiqaeeYsyYMUyYMIHbbruN2NhYMjIyOHDggDkPy7bR0dE0b96cN954g/j4eETkHxuLuLIxC7h2/tXVmMasI7AoO2Jrez1HEO2wa6WmpkpAQIBkZWWJiMjEiRPNa/yfeOIJ+fHHH2Xv3r0SGhoq+fn55faXkZEhHh4e5vPIyEiZOHGi5OfnS4sWLeTkyZPm9z7//PMicwTr1q2Tfv36mc8DAwNl+/btcvLkSWndurVcuXJFPDw8JCsrS37++WfzfEDbtm0lKytLMjMzpX379nLhwgXx8PCQgoICSUpKEl9fXxERGTp0qGzdutXc/8GDB83ag6VLl8qQIUPk0KFD0qtXLxERee+992TSpElW24qINGrUSM6fPy8vv/yyLFq0qNzPpjxc+Rm5iGvnX12NaTYAi4FQB11Pc418+eWXpKam0rdvXwBGjRrF/PnzmTdvHrfffjshISGEhYWRnJxMUFAQAK+++ioNGjRg+/btJZ7zb9iwgXvv/duWetCgQXz33Xf06NGDkSNH0rx581JjWbNmDb6+vubz9957j2eeeYYrV64we/ZslFK8+eab3H333dSoUYOIiAgApk2bRkBAAEopXn/9dW688UYef/xxevToAcC7777LqVOn2LBhA3/++SdgXJ66bNkyunbtiq+vLyLCZ599Rvv27fHy8qJnz57Ur1+fyMjIUtv++9//5u6778bT01PvdaSpUjjcj0BEckxlR0TEuptIMbQfgd6X3RVx5dzBtfN3tB+Bw3UEFmU2DQIaI5cvX+b+++8HID09neDgYPz9/QkPDwfg4sWLJdb7W+Ps2bMEBgbSuXNnJk+e7JDYNRpN5aZCBwIr3gPLlVLLTN4Diyzq1VJKranIa1dncnNz8fLyIioqCjDusOnp6UlcXBxxcXEkJSWxZMkSfHx8iIuLIzExkd9//91qXx999BGhoaEkJCSwfv168xJMjUbjulT0HUFxzcAOIEGM3gPNlVJdlVJ10DqCq8LNzY19+/bRokULc1lmZqZ5omfv3r3mtfNisd7fGlu2bKFPnz7UqFGDoKAgoqOjHZWGRqOppFT0ZHEJzQBwTil1HeAOXBCRbMCgdQS2kfxOyfn1ESNG8OOPPzJo0CDc3NzIzs5m+PDh+Pr6Wl3vb8m5c+do0KAB8PdafI1G49pU6EAgpWgGlFI7gVQROWZrX1pHYCQmJsa8pjg7O9t8PmrUKNzd3XnjjTdITU3l2Weftbrevzi1atVi8+bNpKSk8Ntvv9GmTZtKvVZbryWPcXYYTsOV86/yOgKKeg/cDLgBNTFuLdHLop7WEdhI4Zritm3biojI6tWr5eGHH5acnBxp3769ZGZmWl3vb43XXntN3n77bfO+/ocPH3ZIDteKXkvuurhy/tVhryFL74EJwBAx7jB6Cahjh+u5HP379ycnJ4fAwECmTZtGvXr1GDduHPPnz8fX15fs7GxCQkLYvn17iW2aX3zxRdatW4fBYCA0NJR27fTiLY3G1bGHoMzSeyAR+NrkPXAU4xyC5hop3Ba5Vq1arF1bdM6kVatWxMXFFSnz8/PDz8+vSFmjRo3Ytm2bfQPVaDRVigofCEQkjb9dx/7EuPW0tXr6T1GNRqOpBDhCR1BCM6CUmqSU2qaUWq+UKn8fYxcnPz+/TDHZhg0baNGihdk8pTQVtq31NBqNa2GP5aMhwC8U9R7oUFhBKdUG8BSRQKXUi0ALwObVRK5GdnY2zz33nHlfm0Ix2bx58+jXrx9JSUkAjB07lldffbXc/mytp9FoXAe76wikpPdACNBQKfUT8BfGFUZl4qo6guR3QqlTpw4LFy5k9OjR5vLiYrI6deqwYsUKVq9ezW233cby5ctRSlnt09Z6Go3GdajwTeeUUoeBQGCjiBhMZeYN5pRSU4G2IvK0UioemCQiJWYvi+kIvL799tsKjbMqkZWVxXPPPceSJUvIyspi5syZ1KxZk4KCAnr16sUdd9zBiRMn8PX1JSwsjNGjR9O1a9cS/aSkpNhUrzKRlZVFvXr1yq9YDXHl3MG186+o3Hv16mXTpnP2WDUUC7yK0avYGheAwofTx4BbrVUSkQXAAjDuPuqquxCCUVRWp04dgoODOX/+PKtWraJx48YMGTKE4OBgunXrRr169XBzc8NgMHDLLbdY3bnw3LlzNtWrTOgdKIOdHYbTcOX8HZ27vXUE1tgD9DC9boeeH7gqfvrpJ8aMGUNubi4JCQn4+PjwwQcfsHTpUq5cucKvv/5qVVEM2FxPo9G4FvYYCCx1BCUQkXjgrFJqF3BQRH62QwzVFmtisrCwMD7//HN69uzJwIED6dixI0lJSSVMYqzV02g0GnvrCArL2hU7H1vR163ulCUma968eYl9SVq3bl1CVWytnkaj0djdmMZWjwLN31ia0Fy8eJFXX321iOGMreYyn376Ke3atTPrBjIyMhwSv0ajqVo4wqGsXI8CB8RQZcjOzi5iQrNkyRI6duxYxHDmasxlZsyYQWxsLLGxsebtpzUajcYSR5jXl+tRUF4HrqAjKPQdqFOnDvv27TNvBufm5kZubm4Rw5ktW7YQERFRxFymQ4cOVvudO3cus2fP5u6772bOnDkOy0ej0VQd7D4QyDV6FFjqCBo1asz0zvn2DtWpFH92X+g9cOuttxIfH0/Lli256667OHHiBCkpKRw4cIDMzEzS09PZvXs3Hh4eVvsdPnw4HTt2NBvXNGvWzAHZVBx6T/oYZ4fhNFw5/yrvR2DtwEaPgtIOV/QjKPQemDFjhkycOFFERIYNGyZxcXHi5+cnu3fvFhGRsLAwWbBggdU+Tp06Jfn5+SIi4uvrKzt37nRA5BWL3pPedXHl/KuDH4E1tEfBNZKZmWn2H3ZzcyMrK4uQkBA2btzIlStX2Lp1K7169bLa9uWXXyY2Npbs7Gz++OMP2rdv78jQNRpNFcFRA4GltmAeMMq0vcQ5tEdBmYwbN47Vq1cXMZyxZi5jzYRm6tSpTJ48mYCAAKZPn07Dhg2dlIVGo6nMOGKy2GaPAs3fFOoGWrVqxdy5c4vIza2Zy1gzofH09CQ+Pt7usWo0mqqNvf0IViilvlRK7VBKfa+Uuk4ZKVJWkTFUViy1AYV8+OGH3HPPPQCkpqbSp08ffHx8+Pjjj0vt5/Dhw3h5edGpUyciIsrduFWj0WjKpaIfDRXXDPwCXCciPkB94F7A30pZtaa4NgDg+PHjfPHFF+bziIgIRo0axY4dO1i4cCFZWVlW+5oxYwb/+te/+Pnnn5k9ezYXLpS7+laj0WjKxN5+BBOAjab38kz//gXMKVZWJlVZR1DoKWCpDQAYP348M2fO5IMPPgCME8GXLl3i8uXLAKX6BGzZsoU5c+Zwww030KVLF+Lj4+nbt6/9E9FoNNWWCh0IpKRmYBuAUmogUBv40bRaqEiZtb6qi47Aci1woTZg06ZNNGjQgAsXLpCenk5MTAxeXl4899xzTJ8+nfvvv59du3aZ21muKT579ix79+6lZs2aZGdnExsbi5ubm4Ozchx6LXmMs8NwGq6cf5XXEWChGTCdPwDEADda1ClRVtZRXXQEhdqARx99VPz9/aVnz57i7u4uERER8tRTT0lUVJTk5+fL3XffLcePHze3s1xTfMstt8jZs2dFROS+++6TjRs3OjQHR6PXkrsurpx/ddARmDUDpjuDfwGhIpIJYK3M1YiMjCQ2NpalS5fi5eVFWFgYmZmZXH/99dSsWROlFDk5OVbbFmoILl26REJCAr6+vg6OXqPRVDfssWLHUjMwHmgO/Gh65r0IaFy8TERcfhfSyZMnM3ascXduPz8/OnTowMqVK8nOzubWW/82cZs+fTqPPPIIb731FpMmTXJZKz+NRlNx2NuP4F3TURxrZdWeQm1AIa1atWLTJqOjp5eXFz//XNSj5+GHHwaKzjO0a9eOPXv22DdQjUbjUthbR7BcKVVLKbXGok4/pVSKUirWdFjfLa2aUZ6OYOnSpWbfgCZNmrB161ar/djqRaDRaDS2Ym8dwVaMHsV9itWbLyIBpuMg1RxbdATDhg0z+wY0b94cg8Fgta+r8SLQaDQaW7C3jmCQiEQopY4UqzdIKfUgcAIYbJrdLhVX0BEUcuzYMdzd3UvdF+hqvAg0Go3GFuytIzhhpdpR4DURWauU2g4EYVxKWgRX0xEUsnz5cu64444iZZZriq/Gi6A6oNeSxzg7DKfhyvlXOx2BqeyIxeubATfT60hgaHl9uoKOoJCQkBBJTEws0s5yTbGtXgTVBb2W3HVx5fyrlY6glPdfBoYppWoAnYBf7RBDpcaajgDgwoULpKSk0LFjx1Lb2upFoNFoNLZij4HAUkdgjbnAU8BO4DsR+c0OMVRJNmzYwL33/r0HnzWPAWteBBqNRvNPsLeOoLCsncXrVCC4oq9bFShLRwAwdOhQhg4daj4v9BiwfFZozYtAo9Fo/gnO0BFcr5T6QSmVoJT6WpW2zWYVxlIzkJ+fz5AhQ/D392fUqFGAcV7miSeewMfHhwceeID8fOsT4YX1nn/+eXM9a22rc1lBQUGJz0+j0VQsztARPAakiEgXoCElNQZVmuKagVWrVtGlSxfi4uJITU1l7969xMXFkZ+fz44dO7hw4QIbN2602ldhvU8++cRcz1rb6lwWGxtb4vPTaDQVizN0BL2BFabXW4Be/O1ZYJWqoiOwphno168fAwYMID8/n/Pnz1O/fn3q1q3L+PHjAczG9NZo2rQp48eP59KlS+Z6hWWWbatzmbe3N0FBQUU+P41GU7E4Q0dwM5Bhen0BsLoIvirqCKxpBgoZO3YsN998M3/88Ye5LDw8nNOnT+Pm5lbmmuGoqChzvT///LNE2+pclp2dzc8//1zk87P8DKszrryOHlw7f1fQESzBeKcARgezf5fXZ1XUERRqBs6ePSs5OTlyLSR7AAAgAElEQVRmn4EtW7aIiMjq1aslKChILly4UGY/q1evli5duhSpZ61tdS1btWqV1c/PFXDldfQirp2/o3UE9hgIHgEuA/dalFkOBKOA/zW9XgvcU16fVXkgmDJlinz99dciItKvXz9Zu3atpKamSkBAgGRlZZXZR2G9devWlSizbFudy4YPH17i83MVXPmHUMS183f0QGBvPwJrLAEeVkrtAxKAzXaIodIwbtw4Ro4cybx582jbti19+/Zl9uzZpKammr2GR40aRa9evZg3b14R3cCXX35JamoqkyZN4t///jejRo3izJkzJdpW57KHHnqI+fPnF/n8NBpNxaKMg0blxsPDQw4erPablJZKTEwMwcHBzg7DKejcg50dhtNw5fwrKnel1B4R6V5ePXsoi4sHUlxbcNbCi+CEUuoJe8fgSCw1BGJlXXx6ejrBwcH4+/sTHh5eaj85OTncd999dOnShbfffpuqMGBrNJqqid0HAkpqCyaLyYsA2Af84oAYHEJxDYG1dfGRkZF4enoSFxdHXFwcSUlJVvtavHgxLVq0ICEhgczMzCJeBhqNRlOR2GOOoDjFtQWfACilbgDaici+8jqoCjoCaxoCa+viATIzM82TNHv37qV169Yl+tuyZQuDBg0CoFu3bkRHRxfZh0ij0WgqCrsPBFK6tqAPZUwUVzUdQVkaAst18S1btiQyMpKgoCAKCgrYs2ePVROaw4cPk5ycTExMDDVr1uTXX391yTXVei15jLPDcBqunH+V1xFYO7CuLfgMGGBL+6q2fLRw6ahIyXXx6enpcvr0aRERGTx4sERFRVntY/jw4bJ8+XIRERk7dqxMnTrVzlFXTvQSQtfFlfOvDn4E1ijiUWDaaK4Xxi0mqi2nTp1i1qxZrF27lhtvvBGAn376iTFjxpCbm0tCQgI+Pj5W2xb6DgD83//9n/Yd0Gg0dsNRA0FxbUEPIFFEchx0fadQqAPo27cvAQEBLFq0iP79+5OTk0NgYCDTpk2jXr16JCUlMXHixCJtR4wYwZ9//onBYKB+/fqEhISUchWNRqP5Z9g0R6CUehy4CFzBOPG7SERm2noRKeZRICI/Aw9cXahVh0LfgVdeeYVXXnmlxPtr1xad+G7dunUJAxo3Nzd++OEHwDj/UA1369ZoNJUEW+8IXgC+A54EugBDrVWy0Y9AKaW+VErtUEp9r5RyxMolh1CehsCaN4E1rNVz1bKwsDDtQ6DR2BlbB4IC4EEgC3ADSlvCY4sfgT9wnYj4APWBarEm0hYNgTVvAmsUr3fkyBGrbV2hbO7cudqHQKOxM7b+Nf4yMAyYDgw3/WsNW/wI/gLmmF7n2XLxyqwjSH4nFMAmDYE1bwJrFK93ww03WG3rCmXx8fHah0CjsTM2DQQish3YrpRqgHF+ILuUeuX6EYjIYQCl1ECgNsbBowRVRUdQfK1vWRqC3bt3A9i8t35hvfr165fZtjqXPf/88zRu3NilfAgKceV19ODa+VdKHQFGe8lfgd+AF4FZZdQt04/AdP4AEAPcaMv1q5KOoCwNQWneBMUpXu+DDz6w2tYVyjZt2uRyPgSFuPI6ehHXzr+y6gheBLoBf4nIx0BQGXWLaAaKY7pb+BcQKiKZNl6/ymFNQ/D++++zbNkyatasyQ033EB2ttUbqxL1cnNzrbZ1tTKNRmMnbBktgGjgbtO/LYHNZdS9CeOk8vUWZZbGNK8AR4BY0zGqvOtXxTuCd955R9q2bSv+/v7i7+8vCxculJSUFOnVq5f4+PjIiBEjJD8/X44dOyYTJkwo0kfxeps2bbLa1hXKOnbsaC5zNVz5L2IR187f0XcENvkRKKXaY5wE7gAcBKaIiMMMArQfgd6X3RVx5dzBtfOvlH4EInJYRAaKiKeIPFzaIGCLjsCi7ktKqU22XL8yYqkZsPQOGDlyJCJyTb4DhW01Go3Gkdg0ECilPrOxP1t0BCilWmIUp1VJimsGLL0D0tPTiYqKuibfgcK2Go1G40hs1RGIUqqHiOwqp54tOgIw6gimYNQnlEtl0hFY8x2w9A7o3bs30dHRtGjR4qp9Bwrbat8BjUbjSGwdCOoAm5RSP2Lcc0hEpITuX2zQESilhmM0rf+trAtWVh2BNd8BS++A1NRUDhw4gL+//1X7DhS2Lb5+WK+njnF2GE7BlXMH187f0bnbOhC8ajpsIdZUt7Tn//cBtwN9AQ+lVJiIzC1eSUQWAAvAOFn8wogHbby846hTpw7BwcF06NCBVq1aERwczJ49e6hduzYBAQGsWrWKxo0bM2TIEIKDg61O/lhrW7yenjQLdnYYTsGVcwfXzt/RuduqI2hp5SiNMnUEIjJcjH7Fw4A91gaBqoald8CWLVvo1avXNfkOFLbVaDQaR2LrQNDLdAwAPgSeL6Nuce+Bao+ld8BNN91ESEjINfkOFLbVaDQaR2LrXkMzCl8rpV4F5pVRt4j3gKmsnZV6ycA9tgZaGSn0HbD0DiikVq1aV+07oNFoNM7A1uWjtxcegAfQvpR6xXUEK4p7DyilgpVSsabjhFLqiYpLp+IpTQ/w4Ycfcs89pY9jqamp9OnTBx8fHz7++GMAkpOTCQoKonv37vzv//6vS5ZpNJpKiC3yY4wbyRUenwK9Sqn3L2Ci6fVMYBqwxHQeQzGzemAtYCjv+s7cYmLu3Lny/PPPi4hI37595dixY5KcnCwGg0FCQkJKbTdlyhSJjIwUERGDwSCZmZkybtw42bZtm+Tl5cltt90mImJTWXR09DW3rWxlV4veZsB1ceX8Hb3FhK2Php6yPFdKuZVStbiOYAKw0fReEe8BpdQNQDsR2Vfe9Z2lIyj0GiiuB/jyyy+ZOXMmH3zwQalt3dzcuHTpEpcvXwZAKcWMGTNwd3fn3Llz1K1bF8DlyjQaTeXDVs/i90VkgkXRT0DP4vWkpI5gm6m9Ne+BPsDmMq7pdB1BTEwMLVu2LKEHaNCgARcuXCA9Pb3Utb5eXl4899xzTJ8+nfvvv59du4xavDNnzjB69Ggee+wxc9vyyrKysti/f/81ta2MZVeDXkse4+wwnIYr51+p/AgwWkm2BHZiXPt/O9ARiC+jTRE/AkrxHgA+o9ijotIOZz4aSk9Pl9OnT4uIyODBg6V58+bi7+8vPXv2FHd3d4mIiLDa7qmnnpKoqCjzHvvHjx+XlJQUERE5d+6cNGnSRLKysmwqW7du3TW3rWxlV4t+POC6uHL+lc2PoBfwhmkAeAOYAYwDXiqjjVlHUJr3gFJKmfreYsNY5VSK6wEOHTpEbGwsS5cuxcvLi7CwMKvtMjMzuf7666lZsyZKKXJychgyZAgpKSnUrVuX/Px8rly5YlOZiFxz28pWptFoKiG2jBbAj7bUk2J+BJTiPQB4A9/b2qcz7wjy8vJkwIAB0qNHD/nyyy/N5UlJSebJ4ri4OJk1a1aRdrt375YePXpIjx49ZPz48SIismXLFvH29pZu3brJhx9+aHNZdHT0NbetbGVXi/6r0HVx5fwrpR9BcZRSzUTkVEUMRLag/Qi01N4VceXcwbXzr5R+BEqpcKXUPqXUUaXUUUo3nC/Xj0Ap1VApFaOUilNKvWZjPg7j4sWLPPjgg/j7+zNp0iRz2eDBg8tst3TpUgICAggICKBJkyZs3bqVTz/9lHbt2pnLMzIyHJGCRqPRXBW2bjERBPgBOwAD8Fcp9WzxIxgOJIqIP+CvlCq5N7MTWbJkCT4+PsTFxZGYmMjvv/+Ot7c3e/fuLbPdsGHDiI2NJTY2lubNm2MwGADjEsrC8gYNGjgiBY1Go7kqbN19NB/oCtTFOBDcWko9W/0IbjRNGCtTv9ZdW0w4SkeQ/E6oef2/iJCTk0Pt2rVJTEw0ew+Ux7Fjx3B3dzdvOT137lxmz57N3XffzZw5c+wZvkaj0VwTtnoWNwNuw7iZ3ERgjYgsK6XuYSAQ2CgiBlPZETHtN6SUcge+wji4XAcsFZFIK/1Y6gi8pn/0n6vP7irpfGsD8vPzGTduHNnZ2dx11138z//8D2DcHG7JkiXl9rF8+XIuX77Mo48+yoEDB7h8+TIdO3Zk+PDhzJkzh2bNml11XFlZWdSrV6/8itUQnbtr5g6unX9F5d6rVy+b5ghsWrVjGiw6YfQQ8ATqlVGviI7AVHbE4rU70Nj0ehlwT3nXduSqoRkzZsh//vMfEREZNmyYxMXFiYhI27ZtbWofEhIiiYmJIiJy6tQpyc/PFxERX19f2blz5zXFpFdPuCaunLuIa+df2XQEACilIjBqCGYCbYFvyqheph8BcDfwqWmbii4Y5x0qDYXr/8G4TURWVpbNbS9cuEBKSgodO3YE4OWXXyY2Npbs7Gz++OMP2re3ulefRqPROBVbJ4u7isgg4LyIfI9RK1Aa5fkRrMeoMdgGvCUitv/SOoBx48Yxf/58fH19yc7OtuoPsH379hLbSQNs2LChiN/w1KlTmTx5MgEBAUyfPt2qVaVGo9E4G1sni08ppaYDDU3bRv9ZWkUpx49ARC4DodcQq0No1aoVcXFxJcoLvQcA/Pz88PPzK1Fn6NChDB061Hzu6elJfHy8fQLVaDSaCqLMOwKlVOH+CY8DGUA80AB40r5hOYeYmBjzmv/bbruNL7/80qoXgTXee+89AgMD6d+/P3l5xo1WJ0yYgK+vL08++SQAly9f5qmnnsLLy4tp06YBxsdJDz/8MF26dOHTTz8FICUlhX79+tGpUye+//57APbv30/v3r3p3LkzO3fuBGDTpk0EBQVx1113cfToUQAWL15MUFAQ/v7+pKWlOSS2e++9l4CAALp3766tNjWaKkh5j4aGAohINtBeRJ4XkY9F5JKtFyhFZDZJKbVNKbVeKVX72sOvWIKDg81r/g0GA+fPn8fT05O4uDji4uJISrK+yvXYsWMkJiaybds2+vfvT0pKCtHR0dStW5f4+HhatWrF+fPnWbx4MYGBgezYsYO8vDxEhPfff5+wsDA2b97M2bNnAZg2bRpz585l5cqVpKSkADBlyhRWrlzJf/7zH5KSkhAR3nnnHaKionjrrbc4evQoWVlZREZGsnXrVsaOHcuxY8ccEtvGjRuJjY3llVdeoVu3bg74pjQaTUVi66MhMO46ei0Uisx+wSgs2wj4i0igUupFoAVwrKwOHKEjKPQeALh06RJHjhxhwIABJbwIWrcuqX/bvHkz6enp3H333TRt2pQXXniBhQsXcuTIEXr27Imvry/u7u5s2rSJ2rVrExERwWOPPYZSis2bN3PmzBlefPFF81/iCQkJhIeHs2vXLubPn09eXh7JycmMGjWKQ4cO8e2333LkyBEuXbrEgw8+yNmzZ1mzZg3x8fFcvnyZkJAQrly5wtq1a1myZIldY7NkzZo15jsMjUZTdShvIGiilBqOUfjVzPQaALGy9r8UiovM1mCca/gJo0I5wlojR/sRWO79HRsbyx133GHVi8DahO/OnTvJz8/nzTffZNy4cURERJCQkECTJk14++23GT58OL6+vhw6dIg+ffowePBghg0bhsFg4Pjx4wwdOhQfHx8mTJhAs2bNSExMZPLkyXh6evLSSy8xfvx4kpOTmTVrFlFRUUycOJEBAwaQkpJCeHg4ixYtYurUqdxyyy2kpaXx/vvvEx4ezltvvcXp06ftGluhOU9BQQGbN2/m8ccfr9B91PWe9DHODsNpuHL+js69vIHgG/72J/6vxWubd6qTYmY1QAFwRkQeUErFAwEYVxAVb7cAWADGTedeGPGgrZf8xyxevJjnnnsOPz8/Vq1aRePGjRkyZAjBwcFWN4L69ddf6dChA8HBwXTt2pUmTZpwxx134O3tTUhICO3ataNly5a0bNmShx56CG9vb+rXr0/nzp1p2rQpw4YNo2HDhjz77LMEBwfTrFkzHnnkEQ4fPsyiRYto0qQJt99+O/379+e6667jt99+Izg4mHXr1hESEsKxY8fYs2cPPj4+pKWlERwcTFRUFDfeeCO33HKLXWMr/DxiY2Px9/cv08f5WtAbjwU7Owyn4cr5Ozr3MucIRGRGKcebV3mdWOBVYBNwASjcSvQYpW9X4RREhOjoaHr37l3Ci8DHx8dqGy8vL7MD2ZEjR2jTpo25rKCggD/++IOWLVuayzIyMsjNzaVRo0bmssJ2AHfeeSeJiYnmsjp16lCrVi3OnTtnLmvXrh1//PEHeXl55rKuXbvyyy+/ICIl4rBXbIWsWbOG++67z55fjUajsRe2qM7+6QE8AlwG7gV8gWWm8p2Ad3ntHaks3rlzp9x///0iYt2L4NixYzJhwoQS7caMGSPdu3eXkSNHiohIbm6uDBkyRLp16yZTpkwREZG0tDTp27evGAwGmTdvnogYfQ0CAwOlc+fO8t1334mIyJ49e8Tb21sMBoPEx8dLdHS0rF+/Xrp37y533XWXHD58WEREFi1aJN27dxd/f385c+aMiIiEh4dLjx49pF+/fpKTk2P32Arp1KmTOYaKRKtLXRdXzr9K+BFcLUqpm4A/gEYikqOUmg90B34XkcfLa6/9CPQtsiviyrmDa+dfKf0I/ikikiYi9UQkx3Q+VkR62DII2BvLNfZfffVVCU8Ba5w9e5bAwEA6d+7M5MmTHRyxRqPRVCwVOhBY0QysUEp9qZTaoZT6Xil1XWUypim+xj4gIMCqp0BxPvroI0JDQ0lISGD9+vUcOnTIwZFrNBpNxXE1OgJbKK4Z+AW4U0R8lFIxGOcIWmM0phmnlNqglGotIg73I0h+J9Tq+n8o6SlQnC1bthAREUGNGjUICgoiOjqaDh06VGh8Go1G4yjsMRBYagYmYBSQAeRZ1CvXmMbeOoKYmBir6/8NBgPLly/njjvuKHUdb0pKCgcOHCAzM5P09HR2796Nh4dHhcZniV5PHePsMJyCK+cOrp2/w3O3ZUb5ag7gMNAM2GdRNhCIAWpi9CP4Hlhp+nd4eX3aa9VQRESEvPvuuyIiMnz4cPnmm29EpKingDX8/Pxk9+7dIiISFhYmCxYssEt8hejVE66JK+cu4tr5V0o/gqvEUjOAUuoBYDxwv4gUmOo8LSIPY9yu+rQdYrAJa2vsi3sKWCMkJISNGzdy5coVtm7dqjda02g0VRp7DARmYxqTmvhfQKiIZJrerzTGNL6+vjRq1IgePXrg4eGBt7d3CU8Ba94DL774IuvWrcNgMBAaGmqzn7FGo9FURip6jgCKGtOMB5oDPxqnBFgEfA08RyUxpim+cVpxTwFr3gONGjVi27YSu2JoNBpNlaTC7wjEQjMgIu+KSDsRCTAdi0TksoiEioi3iHxV0de/Giw1BBkZGdx///306NGDZ599ttQ2WkOg0WiqG3YXlFnzIzC9fkkptcne1y+N4hqCOXPmYDAY2LVrF1FRUfz2229W22kNgUajqW44QllcqC0Ao7Zgg1KqJU52ObPUEGzbto3Q0FBGjhwJQO3apXvlbNmyhT59+hTREGg0Gk1Vxh5zBMUpri34BKMHwRTg5dIaFdcRRCxZXWEBdb61QQkNQVxcHAaDgblz59KiRQtOnz7N6dMlFzQ5WkMAej21zt01ceX8K5sfwT9GSvoRBAIJgPVnL3+3s6sfgTUPgd9//53U1FQ2bNhArVq1rLa77bbbuOOOO/Dy8mLFihUYDAa7b4ylN98KdnYYTsGVcwfXzr9S+RFUIJbagvsw3hksBbyUUmEOiqEIxTUEzZs3Z+3atXz77belDgKgNQQajab64aiBwKwtEJHhIhIADAP2iMhcB8VQhOIagqVLl5KcnExQUBABAQGsX79eawg0Go1L4Ig5AiiqLag0FNcQWENrCDQaTXXHKX4EprJkEalYg9urwFJDcPr0aZu0AVpDoNFoqiPO8COoq5RabfIjeK8ir28rxTUE//M//2OTNkBrCDQaTXWkou8IimsGfgGuExEfoD5GP4IRwA4R8Qc8lVJ3VnAM5VJcQ5CUlGSTNkBrCDQaTXXEGX4EucANJj+C6ynqU2DGXjoCaxqCAwcO2KQNcIaGAPR6ap27a+LK+VdpHUFxzYCIbANQSg0EamMcKGoA8cAQYLOIHC2lL7vpCIprCHJycmzSBjhDQwB6PbXO3TVx5fyrg46gPD+CKcCnInIHcJNSyq/UnuxEcQ2Bh4eHTdoArSHQaDTVEWf4EdwIFK4eygXq2SGGMimuIfjqq69KaAO0hkCj0bgKzvAjmAcsUUqNA/4ANtshhnIpriEorg3QPgQajcZVcIYfQbKI+IuIr4g8YmFf6TA2bNhAixYtCAgIICAggJ07dxIcHIy/vz/h4eFltrXUH+TlGee5J0yYgK+vL08++SQAly9f5qmnnsLLy4tp06YBcOHCBR5++GG6dOnCp59+Chgnn/v160enTp34/vvvAdi/fz+9e/emc+fO7Ny5E4A9e/YQFBTEXXfdxdGjximVxYsXExQUhL+/P2lpaU6LDWD37t1cf/311/htaDQaZ2NvHcFypdQyk2Zgkan8eqXUD0qpBKXU16bVQw5n7NixxMbGEhsby+7du/H09CQuLo64uDiSkpKstimuP0hJSSE6Opq6desSHx9Pq1atOH/+PIsXLyYwMJAdO3aQl5eHiPD+++8TFhbG5s2bOXv2LADTpk1j7ty5rFy5kpSUFACmTJnCypUr+c9//kNSUhIiQmRkJFFRUbz11lscPXqUrKwsIiMj2bp1K2PHjuXYsWNOiQ0gPz+fSZMmUb9+fXt/ZRqNxk7YW0ewA0gwaQaaK6W6Ao8BKSLSBWhoqudwVqxYgbe3N4MGDQIgMzMTEUFE2Lt3r9U2xfUHrVu3ZtOmTRw8eJCePXty/vx53N3d2bRpE9u2bcPb25umTZuilGLz5s0sX76c4OBg89xCQkIC4eHhPPTQQ3h6epKXl0dycjKjRo1i9OjRGAwGjhw5Qm5uLg8++CCvv/46BoOB+Ph4Ll++TEhICAsXLqRjx45OiQ3g/fffZ8SIEXog0GiqMPbWEQwCzimlrgPcgQtAb2CFqf4WoBd/aw3M2FNHcPbsWYYMGYKvry9hYWF069aNo0ePEhQUREFBAXv27KFhw4Yl2hbXH0RERJCQkECTJk14++23GT58OL6+vhw6dIg+ffowePBghg0bhsFg4Pjx4wwdOhQfHx8mTJhAs2bNSExMZPLkyXh6evLSSy8xdepUkpOTmTVrFlFRUUycOJEBAwZw/vx55syZw6JFi5g6dSq33HILaWlpvP/++4SHh/PWW29x+vRph8c2YsQIvvvuO2bOnEl2drZd1j3rteQxzg7Dabhy/g7PvfCv4Io6gMNAM2CfRdlOYJXp9Y/APabXo4H/La/PDh06SEVy9uxZycnJERGRRx99VP773//K6dOnRURk8ODBEhUVZbVdRESEvPvuuyIiMnz4cPnmm29kwoQJ8t///ldERPz8/CQ+Pl4GDRokO3fuFBGRW265RVJTU8XLy0v++usvycvLEzc3NxERue2220RE5NChQ+Lh4SGZmZly5513iojIxo0bpW/fvrJ//37p2bOniIgsWLBAnnvuOVmzZo2MHTtWRESmTp0qM2fOdEpsc+bMES8vLwkKCpLrr79enn766X/4zZQkOjq6wvusKrhy7iKunX9F5Q7sFht+t+2qI1BK3ayUcgP8gIZKqV7AWaCBqW4D07lD+eCDD1i6dClXrlzh119/5dSpU4wZM4bc3FwSEhLw8fGx2q64/qBNmzbmsoKCAv744w9atmxpLsvIyCA3N5dGjRqZywrbAdx5550kJiaay+rVq0etWrU4d+6cuaxdu3b89ddf5OXlmcu6du3KL7/8goiUiMORsb344ovs3r2bmJgYbr31Vj777DMHfHsajabCsWW0uJoDeAS4jHFfobeBx0zl64EBwChMdwHAWkx3B2UdFX1HcPLkSQkKCpLu3bvL9OnTJS8vTwYMGCA9evSQL7/8UkREjh07JhMmTCjRdsyYMdK9e3cZOXKkiIjk5ubKkCFDpFu3bjJlyhQREUlLS5O+ffuKwWCQefPmiYhIUlKSBAYGSufOneW7774TEZE9e/aIt7e3GAwGiY+PFxGR9evXS/fu3eWuu+6Sw4cPi4jIpEmTpHv37uLv7y9nzpwREZHw8HDp0aOH9OvXz3x344zYCmnbtu0/+1JKQf9V6Lq4cv6OviNQxroVh1LqJoz6gEbAzcDXQB3gKPAExnmJFcDtGC0rH5dygvDw8JCDBw9WaJxVCS21D3Z2GE7BlXMH186/onJXSu0Rke7l1atwQZmIpPG3WvhPjJPDlhRgtKt0OBs2bGD06NG0atUKgCFDhjBr1izz+cKFC61uIpeTk8PgwYM5ceIEBoOBr776CietetVoNJoKx+F+BKb3aiml1lTktW3FUj/g4eFR4twaixcvpkWLFiQkJJCenk5UVJSDo9ZoNBr74XA/AqVUHWAPlUA/ICIlzq1R6EMA0Lt3b+1DoNFoqhUO9yMQkWzAoJQ6UlZH9tARNJTMIvqBzZs3FzmfM2cOXbt2LdHu8OHDJCcnExMTQ2pqKgcOHHDoGl+9njrG2WE4BVfOHVw7f1fwI7C1rwr3Izh37hz16tXDzc0Ng8FAjx49eOihh8znt9xyi9UJmg4dOtCqVSuCg4PZs2cPtWvXdugklp40C3Z2GE7BlXMH187fFfwInEZx/cDSpUuLnHfq1Mlqu0IfAjA+JtI+BBqNpjrhDD8CpxEWFsbnn39Oz549GThwIJ988kmR844dO5KUlMTEiROLtBsxYgR//vknBoOBm266iZCQkFKuoNFoNFUPh/sRiMgiO1zTJpo3b17iuVvx89atW5cwpHFzc+OHH36wc3QajUbjHBzuR2BRz+H2Xh9++CH33HMPS5cuNXsRNGnShK1bt1qt/+mnn9KuXTtz3YyMDAdHrNFoNPanQu8IlFKbgH+JyC9Kqd7A84AAtwAHRWSUyX/gC8ADOK19F9EAAA2CSURBVA08LCL5FRmHNY4fP84XX3xB48aNGTZsGMOGDQOgS5cu5i2VrTFjxgxGjBhh7/A0Go3GaTjDj8CfYtqCCo7BKuPHj2fmzJlFyo4dO4a7u7vVLacLmTt3Lt26dWP8+PH2DlGj0WicgjP8CC4Cc0z182zpNPtyAa0mr72mgJLfCSUyMpIuXbrQsWPHIu+tWbOG0NDQUtt6eXnRuXNnfHx8aN26NS+99JJ5OwqNRqOpLthj07nDQCCwUUQMprKdQKqIPGRRbyDGyeQQa8tKLQVljRs39vr222+vOabw8HBOnz5NQUEBJ06cYNSoUQwcOJAJEybwwgsvlPrjnpaWRoMGDahZsyZhYWGMGzeOO++885rjuFaysrKoV69e+RWrITp318wdXDv/isq9V69eNm06Z49tqD8HIoAPMO4+6gbUBLYCvUx1HgBigBtt6bOitqFOSkqSkJAQERHJyMgQDw+PMusPHz5cYmJi5NKlS3LrrbdKWlpahcRxtejteF0TV85dxLXzd/Q21PZYProBWAyEYtxi4jcRWayUugTUsdAW9BORi3a4vm1BbtjAvff+PT2xfft2tm/fXkRDMHXqVEaPHk1eXh7Tp08vcy5Bo9Foqir21hEkAl8rpcZh9CP4EZiIk7QFrVq1YtOmTQAMHTqUoUOHmt/z8/PDz8+vSH1PT0/i4+MdEZpGo9E4DXvrCP4Ukd4i4isij4lIgZShLbAnhRoCW7UBZ8+eJTAwkM6dOzN58mRHhKjRaDROwd5+BMuLew8opYKVUrGm44RS6omKjMEahRqCQmbMmGH2IGjQoIHVNh999BGhoaEkJCSwfv16Dh06ZO8wNRqNxinYW0ewlWLeAyISU3g3AOzD6FlgV4prCGzRBhR6ENSoUYOgoCDtQaDRaKotdtcRiEiENe8BpdQNQDsR2Vdep9eqI7CmIbBVG3Du3Dnz3UL9+vVJS0u76utrNBpNVcDefgQnyqjeB9hc2pvFdAR826/uVccTExPDwoULOX36NMuWLePEiRN88sknPPbYY2zbto369euzfv16q9qAWrVqsXnzZlJSUvjtt99o06aN00wytEFHjLPDcAqunDu4dv4Oz92WNaZXc2ChI7AoO2Kl3mfAAFv6rAgdQaGGwFZtwGuvvSZvv/22FBQUSOfOneXw4cP/OIZrRa+ndk1cOXcR187f0ToCu/oRlFbBtPFcL2CLHa5fJlOnTmXy5MkEBASYtQHbt28vsfX0iy++yLp16zAYDISGhtKuncM3S9VoNBqHYG8dQWn0ABJFJMcO17eKpYaguDbAmoagUaNGbNu2zVHhaTQajdOwq47AoqxdsTo/i8gDFX3t0ijUEABcvHiRwYMHl1lfawg0Go0r4QgdwTKlVJxSapFFvUlKqW1KqfVKqdoVGUNxLDUESUlJeHt7s3fv3jLbaA2BRqNxJRzuR6CUagN4ikggsB5oUcExFMFSQ9C6dWsSExPLbaM1BBqNxpVwhh9BCNBQKfUT8BfGFUZlci06grJ8CMpDawg0Go0r4RAdgYUfwTGl1DDgjIg8oJSKBwKAErOy/1RHYE1DMH78eAYOHEh2dnaZa3Qrk4YA9Hpqnbtr4sr5VysdAVb8CIAw+P/27j+2qruM4/j7EUZXxC5S0AglG4HQBbDF+AMKOksx/FrnJKTJMsQfJJpUmD8YUwnGLBEiGknAZEYJAY1skoAGRmcqaKkRBDtQ2LqNBjIIGUENBdxQ2FJ5/OMc4Pb2UAre03t7v59X0vScc8+5/T4Hbp97bs/zffhmvO+zwGO3e87/t44gsw+Bu/u4ceN63b+QagjcdT91qEKO3T3s+IutjuBJoMGjDmT/AUqJ5h76aLzveOD1FMbQZ6ohEJHQ9Xs/Anf/r5mdN7MXgdfcvS2FMXSTWUMAcPLkzamPVEMgIqHLeSJw9wvA9WabZ4G6hH0ac/1zRUTk7uSjH8HgpNqCXOrq6qKhoYEZM2awZMkSmpubqaiouNGMpqOjI/G4q1evUl9fT3V1NYsXL77+Nw8RkaLW7/0IgM+QVVuQ4zGwc+dOqqurOXDgAOfOnePo0aM0NjbeaEZTWVmZeNzWrVupqKjg2LFjXLx4kb179+Z6aCIiBScf/Qiagd9m1Rb06k7qCE6vfZi5c+cyf/58urq6uHTpEmVlZWzatIldu3YxZswYduzYQdwvuZuWlhYWLlwIQF1dHfv27evW4F5EpBj1ez8Cd78M3WsLkp7rbusIMu+9bWxspLy8nLKyMhoaGqipqWHZsmVs2LCBKVN6XoicOHGC06dP09rayrlz5zh+/HhB3Mes+6lb8z2MvAg5dgg7/v6OPY27hvYDq4DfJz1oZuXAZWA60GJmM929xxwO7r4R2AhQWVnptbW1fR5AZ2cnw4YNo729nbq6OkpLS1m+fDklJSVUVVUxatQokp5vwoQJPPDAA9TW1nLkyBGGDBmSuF9/a21tLYhx5INir833MPIm5Pj7O/Z89CNIqi3IqXXr1rF9+3YGDRrE0KFDWb16Ndu2bePatWu0t7czefLkxONmzZrFnj17gOhjopkzZ+Z6aCIiBSeNRHC7fgTPAEvi6SU6if6ukFNLly5l8+bN1NTUUF5eTlNTE1u2bGHq1KksWLCAiRMncurUKVasWNHtuEWLFnH27FmqqqoYPnw4s2bNusVPEBEpHmnXEVzfNj5jObG2IJdGjx5NS0v35mfZn7eNHTu2R0VxSUkJTU1NaQ5NRKTgpF1H8Gsz+4WZHTKz5+M7hVLtR5BdQ5C9fiuqIRCRUKVdR/A3YLC7TwPKgNlp9yPIriFYv359j5qCJKohEJFQpV1H8CSwJ37snfh7qv0I2r/TvYZg9uzZjB8/vltNQRLVEIhIqNKuI/gTgJktAIYQJYpvcYf9CEaMGMl3P9jVpzEcPnwYuFlDcOHCBdra2m6snzlzhjNnzvQ4rlBrCED3Uyv2MIUcf9HVEZjZp4GvAY/EM4++CVyf7Od1YHTSk2TXETyx6NE+/fDsGoLOzk7q6+tvrLt74m2hhVpDALqfWrGHKeT4i6qOIL4yeAp42N3fih9PtR9Bdg3BmjVruq1fuXIl8TjVEIhIqNKuI/g88AHgd2a238yWuPtB4Ho/go5c9yPIriHYvXt3t/U5c+aohkBEJEPadQQ/iL+y90mtH0FSDUH2umoIRERuSuOKQEREBhAlAhGRwCkRiIgEzgbCVApm9hY3bzkN0QjgfL4HkSeKPVwhx5+r2O9395G32ymNOoI0dLj7R/I9iHwxs8Ohxq/Yw4wdwo6/v2PXR0MiIoFTIhARCdxASQQb8z2APAs5fsUerpDj79fYB8Qfi0VEJD0D5YpARERSokQgIhK4gk4EZnavmTWZ2TEz+6WZWb7HlBaLZLb1HJYde7GfDzP7RtzudETcyvRlM1sbP9ZjW7HIat36vlBiN7N3m9kuMztgZj8M6d/dzO4xs93xco/XdV+35Wo8BZ0IgM8Cb7h7NfBeovaXxWoG3dt6LqFn7EV7PszsfuAL8erXgReAamCemU24xbYBL6F163oCiR1YBBxy9xnAJOBnBBC7mZUSTcd//fWb9Lru67acKPREUEc0rTVAC1DMTQL+AWyIl98BnqZn7MV8PjYAK+PlOmCvu18D/khG7FnbikFm69ZPAGMJJ/a3gaHxO9t7gekEELu7X3H3KuCNeFPS67qv23Ki0BNBOfCvePlNYHgex5Iqdz/h7m0ZbT2P0DP2ojwfZvY4cAx4Nd6UFGdRxg6MJGrd+hBQAXyMcGJ/DpgHvAYcJ4otlNgz9fX/e2rnotATwXngvnj5Pop83pHMtp7AP+kZe7Gej3qid8bbgA8TzbMSSuzZrVtPE07sK4GfuvuDRL/UJhBO7JmSYuzrtpwo9ETwB2B2vFwH7MvjWFKV0NYzKfaiPB/u/ri7fxx4jOhK6Blgtpm9C/gkGbFnbSsG2a1bOwgn9vcAV+Plt4GDhBN7pr6+1lN7/Rd6IngWGG1mLwEXiE5EserW1hO4h56xh3I+fgzMB14CXnD3k7fYNuBlt24FPkcgsRMl/EYzOwiUAgsIJ/ZMSa/rvm7LCVUWi4gErtCvCEREJGVKBCIigVMiEBEJnBKBiEjglAgkWGb2tJl1mNn++Our+R6TSD4MlJ7FImn5nrtvzfcgRPJJVwQitxHP+rjbzP5sZjvMbHC8bZuZHYxniy01sxIz+1U8m+ZzZjYkPr7VzL5vZs3x+vvNrNnM/mJmK3v/6SLpUyKQ0K2Kf1H/pJd9JgHu7tOBTcAw4MvAMXevAZ4HqoAvAa/Gs2meAL4YHz8VeNHd58brK4Ft7j4VeNTMynMelcgdUCKQ0K1x91p3/0ov+/wVeDmeP34e8G/gQaAtfnwzcBiYSDRNAvH3ifHyK+7+m4znqySqqG0lSiqjchGIyN1SIhC5vSlE8+Y/QjQh3kNEs2VOjR9fRfTu/xVgWrxtWrwOcDnr+TqAb7t7LfAj4GJqIxfpAyUCkds7BTxhZm1E794PAxuBKfG8UB8CthJ9bDTJzA4QzaT581s831rgKTM7BHwK+Hu6wxfpneYaEhEJnK4IREQCp0QgIhI4JQIRkcApEYiIBE6JQEQkcEoEIiKB+x+z2BcSG/DbjwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from xgboost import plot_importance\n",
    "from matplotlib import pyplot\n",
    "\n",
    "# 找出最重要的特征\n",
    "plot_importance(bst, importance_type = 'cover')\n",
    "pyplot.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
